In the era dominated by intelligentization, the importance of digital images can never be overemphasized. The technology of facial recognition, which can automatically recognize people's identity with facial images, is widely applied in the fields including intelligent security, identity authentication, and internet finance, etc. However, methods for spoofing the facial recognition system emerge one after another. For example, the recognition system may be deceived by facial photos and mistakenly determine that the individual is who he/she claims to be on the spot while he/she does not show up. This deficiency has made the security of the facial recognition system highly questionable. In addition to the deception on the facial recognition system, the authenticity of the facial image itself is also a matter of great concern. Today, as image editing software, such as ADOBE PHOTOSHOP, becomes increasingly accessible, the tampering of image content seriously threatens the fields such as media and publishing industry, court forensics, insurance industry and other industries that are highly dependent on image credibility. Among them, facial image tampering, such as image recapturing and face splicing, is more dangerous. This is also an important topic in the field of digital image forensics. The photo spoof detection of the facial recognition system is also called living body detection, which is essentially an image recapture detection, and belongs to the category of image forensics.
At present, the disclosed live facial detection technology mainly uses a machine learning framework of feature design+classification, and texture characteristics, dynamic characteristics and the like are mainly considered. The following literatures may be referred: Wen, Di, H. Han, and A. K. Jain. “Face Spoof Detection With Image Distortion Analysis.” Information Forensics & Security IEEE Transactions on 10.4(2015):746-761. and Tirunagari, Santosh, et al. “Detection of Face Spoofing Using Visual Dynamics.” Information Forensics & Security IEEE Transactions on 10.4(2015):762-777. In the field of image forensics, tampering detection technique for facial images and videos involves the use of illumination inconsistencies, human pulse signals, etc., which may be referred to in: B. Peng, W. Wang, J. Dong, and T. Tan, “Optimized 3D Lighting Environment Estimation for Image Forgery Detection,” IEEE Transactions on Information Forensics and Security, vol. 12, pp. 479-494, 2017. and B. Peng, W. Wang, J. Dong, and T. Tan, “Detection of computer generated faces in videos based on pulse signal,” in 2015 IEEE China Summit and International Conference on Signal and Information Processing (ChinaSIP), 2015, pp. 841-845.
The present disclosure proposes a perspective distortion characteristic based facial image authentication method to effectively perform facial image authentication and can be applied to the fields of live face detection and facial image tampering detection, etc.